Human-based image analysis is a commonly performed task in many contemporary professions. For instance, radiologists and other medical professionals frequently examine medical images to diagnose and treat patients, airport security agents scan x-rays of luggage for prohibited items, and factory workers perform visual inspection of goods to assure quality. In these tasks, the human examiner must combine their knowledge of the domain and a high degree of mental concentration within a short amount of time to classify or interpret the images. While there have been many advances both in the technology used to create images and in the training of human examiners, many image analysis tasks are still prone to significant error. For example, some studies have shown that radiological image examination still has error rates nearing twenty percent for clinically significant errors. Moreover, even with examination of an image by multiple users the error rate is often still quite high.